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planning-with-files

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Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same-project local agent session records and emits aggregate counts only; --replay may emit bounded nonce-framed excerpts. Optional gated mode can request continuation only when the host supports it and never runs commands declared in Markdown. The skill has no network upload path. Use for research or work needing 5+ tool calls.

.mastracode/skills/planning-with-files/SKILL.md

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Network or broad shell
Last checked
Nov 9, 2026

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27,979
Repository last updated
Nov 7, 2026
License
MIT

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# Planning with Files

Work like Manus: Use persistent markdown files as your "working memory on disk."

## FIRST: Restore Project State

**Before continuing**, resolve the plan this task owns. Use the installed `scripts/resolve-plan-dir.sh` (or `.ps1`) with the host's `PLAN_ID` and `PWF_PLAN_ROOT`, then read `task_plan.md`, `progress.md`, and `findings.md` from that selected directory. If an explicit selector is rejected, or multiple named plans exist without `PLAN_ID`, correct the pin and do not fall back to another task. Run `git diff --stat` for code changes not yet recorded there. All planning filenames below mean that selected directory. For parallel tasks, pin each host before it starts or use separate worktrees; a child process export does not change its host. One orchestrator owns a shared plan and summaries, while workers use assigned files or ledgers.

```bash
# Linux/macOS
$(command -v python3 || command -v python) ~/.mastracode/skills/planning-with-files/scripts/session-catchup.py --metadata "$(pwd)"
```

```powershell
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